Users are increasingly utilizing electronic devices to obtain various types of information. For example, a user wanting to obtain information about a book can capture an image of the cover of the book and upload that image to a book identification service for analysis. In many cases, the cover image will be matched against a set of two-dimensional images including views of objects from a particular orientation. While books are relatively easy to match, as a user will generally capture an image of the cover of the book with the cover relatively centered and upright in the image, other objects are not as straightforward. For example, an object such as a pair of boots might be imaged from several different orientations, with many of those orientations not matching the orientation of a stored image for that type or style of boot. For example, a top view of a pair of boots will look substantially different than a side view of the pair of boots, which can cause problems if an image of the pair of boots used for image matching only represents one view. In some cases a matching algorithm might utilize multiple views of various products to assist with the matching, but providing additional views rapidly expands the number of images that must be searched, which increases the amount of latency in receiving results, requires more processing power and storage, and can potentially result in more false positives through matching with these additional images.